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	Overview  outcomes  stats  drivers teams seasons teammates regulations serieses career gaps cs positions age weather events  search  imprint		# company point c victories poles fl pod entr qual % class % 1 Ferrari 8438.3  (8594.8) 23 235 215 240 753 2081 2053 (98.7%) 1491 (71.6%) 2 McLaren 5348.5  (4944.5) 9 175 154 148 465 1654 1625 (98.2%) 1135 (68.6%) 3 Williams 3573.5  (3595.5) 9 114 126 134 314 1540 1510 (98.1%) 1041 (67.6%) 4 Lotus 2087.0  (2111.0) 3 75 98 70 189 1259 1195 (94.9%) 691 (54.9%) 5 Sauber 547.0 0 0 3 10 779 774 (99.4%) 525 (67.4%) 6 Tyrrell 739.0 2 24 15 20 81 896 848 (94.6%) 463 (51.7%) 7 Renault 1495.0 2 35 51 31 99 705 700 (99.3%) 460 (65.2%) 8 Red Bull 4275.0 4 59 59 50 159 530 530 (100.0%) 428 (80.8%) 9 Toro Rosso 413.0 1 1 0 1 493 491 (99.6%) 362 (73.4%) 10 Benetton 870.5  (871.5) 1 27 14 36 103 584 582 (99.7%) 357 (61.1%) 11 India 1090.0 0 1 4 6 425 425 (100.0%) 347 (81.6%) 12 Mercedes 4468.0  (4484.1) 4 86 101 46 178 391 390 (99.7%) 341 (87.2%) 13 Ligier 387.0  (389.0) 9 9 9 50 626 587 (93.8%) 316 (50.5%) 14 Minardi 38.0 0 0 0 0 676 637 (94.2%) 302 (44.7%) 15 Arrows 142.0 0 1 0 8 595 550 (92.4%) 279 (46.9%) 16 Jordan 288.0 4 2 2 19 501 492 (98.2%) 275 (54.9%) 17 Toyota 286.0 0 3 3 13 280 280 (100.0%) 202 (72.1%) 18 MRD 241.0 9 17 12 29 403 369 (91.6%) 170 (42.2%) 19 Brabham 583.0  (588.0) 2 24 19 25 77 320 308 (96.2%) 162 (50.6%) 20 March 131.0 2 2 4 14 411 352 (85.6%) 159 (38.7%) 21 BAR 227.0 0 2 0 15 236 234 (99.2%) 140 (59.3%) 22 Cooper Car Co 348.5  (361.5) 1 12 5 9 46 237 226 (95.4%) 139 (58.6%) 23 Marussia 3.0 0 0 0 0 173 172 (99.4%) 138 (79.8%) 24 Arthur Owen 386.0  (411.0) 3 13 9 12 53 266 247 (92.9%) 135 (50.8%) 25 BMW 314.0 1 1 2 17 145 142 (97.9%) 122 (84.1%) 26 Team Surtees 55.0 0 0 3 2 248 217 (87.5%) 116 (46.8%) 27 BRM 106.0 4 2 2 8 234 209 (89.3%) 102 (43.6%) 28 Honda 154.0 3 2 2 9 151 151 (100.0%) 101 (66.9%) 29 Shadow 68.5 1 3 2 7 226 199 (88.1%) 99 (43.8%) 30 Haas F1 176.0 0 0 1 0 122 122 (100.0%) 97 (79.5%) 31 Jaguar 49.0 0 0 0 2 171 170 (99.4%) 96 (56.1%) 32 Maserati 250.3  (259.8) 1 9 9 11 37 166 160 (96.4%) 95 (57.2%) 33 Larrousse 23.0  (25.0) 0 0 0 1 242 222 (91.7%) 92 (38.0%) 34 Prost 35.0 0 0 0 3 166 165 (99.4%) 90 (54.2%) 35 Caterham 0.0 0 0 0 0 107 107 (100.0%) 83 (77.6%) 36 Footwork 25.0 0 0 0 1 194 172 (88.7%) 82 (42.3%) 37 Matra 184.0 1 9 4 12 21 117 112 (95.7%) 78 (66.7%) Alfa Romeo 190.0  (203.0) 1 11 11 14 27 174 171 (98.3%) 78 (44.8%) 39 Walker 158.0 9 8 7 16 154 137 (89.0%) 77 (50.0%) 40 HRT 0.0 0 0 0 0 114 110 (96.5%) 75 (65.8%) 41 Fittipaldi 44.0 0 0 0 3 156 121 (77.6%) 70 (44.9%) 42 Dallara 15.0 0 0 0 2 144 133 (92.4%) 61 (42.4%) 43 Martini Racing 100.0 2 2 3 13 118 108 (91.5%) 51 (43.2%) ATS 8.0  (9.0) 0 0 0 0 161 122 (75.8%) 51 (31.7%)
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prog="f1stat": Connect to MySQL Database on /clx/sys/fifo/mysql.sock...
db_default:FALK
login:, bid:
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Jetzt: 1542538743
Cache: 
Anfangszeit: 1542538743.3782
MP LOGGED_IN:
PHP_SELF::/stats/teams/classified SCRIPT_URL:/stats/teams/classified
URL:stats:7:
URL:teams:2:
URL:classified::
### URL: //stats/teams index: 2 Skript: "Statistik/Fahrer_Teams.php" Header: ".php" 
stats
select kurzname, tmp_team, tmp_team as wer, tmp_kwms as wms,  max(f1_Rennen) as letztes, aktiv is not null as akt, sum(wmpunkte) as wmpunkte, sum(punkte) as punkte, sum(k = 1) as siege, sum(q = 1) as poles, sum(k >= 1 and k <= 3) as podeste, sum(tmp_spos = 1) as srunden, count(f1_Rennergebnis) as gemeldet, sum(q > 0 or runden > 0) as qualifiziert, sum(k > 0) as klassifiziert, (sum(q > 0 or runden > 0) / count(f1_Rennergebnis)) as qual_p, (sum(k>0)/count(f1_Rennergebnis)) as klass_p from f1_Rennergebnis left join f1_Firma on f1_Firma.f1_Firma = tmp_team group by tmp_team having klassifiziert >= 50 order by klassifiziert desc, letztes; -- 119.825 ms
Kein passender Alias für "-615" (Typ:f) gefunden!
Kein passender Alias für "-615" (Typ:f) gefunden!
Kein passender Alias für "-616" (Typ:f) gefunden!
Kein passender Alias für "-616" (Typ:f) gefunden!